Toward spectrometerless instant Raman identification with tailored metasurfaces-powered guided-mode resonances (GMR) filters

Abstract

Abstract Raman identification is an instrumental tool with a broad range of applications, yet current spectroscopy approaches fall short in facilitating practical and scalable Raman identification platforms. In this work, we introduce a spectrometerless Raman identification approach that utilizes guided-mode resonance filters. Unlike arrayed narrowband-filters spectrometer, we tailor the transmission characteristics of each filter to match the Raman signature of a given target. Hence, instantaneous Raman identification could be directly achieved at the hardware level with no spectral data post-processing. The filters consist of a metasurface grating encapsulated between two identical distributed Bragg reflectors and are characterized by transmission peaks line-widths narrower than 0.01 nm and transmission efficiency exceeding 98%. We develop a rigorous design methodology to customize the filters’ characteristics such that the maximum optical transmission through a given filter is only attained when exposed to the Raman scattering from its matched target. To illustrate the potential of our approach, we theoretically investigate the identification of four different saccharides as well as the classification of two antibiotic-susceptible and resistant strains of Staphylococcus aureus. We show that our proposed approach can accurately identify these targets. Our work lays the foundation for a new-generation of scalable, compact, and cost-effective instant Raman identification platforms that can be adopted in countless applications from wearables and point-of-care diagnostics to in-line quality control in food and pharmaceutical industries.